Artikel

Using variable slope total derivative estimations to pick between and improve macro models

Using the same data set, a researcher can obtain very different reduced form estimates just by assuming different macroeconomic models. Reiterative Truncated Projected Least Squares (RTPLS) or Variable Slope Generalized Least Squares (VSGLS) can be used to estimate total derivatives that are not model dependent. These estimates can be used to pick between competing macro models, improve current models, or create new models. A selected survey of RTPLS estimates in the literature reveals several common patterns: (1) as income inequality has surged around the world, the effect of changes in government spending (G), exports (X), and money supply (M-1) on Gross Domestic Product (GDP) have plummeted, (2) decreases in G, X, and M-1 cause GDP to fall more than equal increases in G, X, and M-1 cause GDP to rise, and (3) unusually large increases in G and M-1 cause their effect on GDP to plummet. These common patterns fit with a global glut of savings hypothesis, which predicts that an increase in savings will not cause an increase in production expanding investment. An appropriate model could be built around the idea that investors have a choice between investing to increase production or investing to earn rent or interest.

Sprache
Englisch

Erschienen in
Journal: Journal of Risk and Financial Management ; ISSN: 1911-8074 ; Volume: 15 ; Year: 2022 ; Issue: 6 ; Pages: 1-13

Klassifikation
Management
Thema
choosing between macro models
export multipliers
global glut of savings
government multipliers
investment to own or rent
Keynesian model
money supply multipliers
omitted variables bias
production expanding investment
total derivatives

Ereignis
Geistige Schöpfung
(wer)
Leightner, Jonathan Edward
Ereignis
Veröffentlichung
(wer)
MDPI
(wo)
Basel
(wann)
2022

DOI
doi:10.3390/jrfm15060267
Handle
Letzte Aktualisierung
10.03.2025, 11:44 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Leightner, Jonathan Edward
  • MDPI

Entstanden

  • 2022

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